Baoshan Yangab,
Hui Wang*ab,
Yingkui Jiangab,
Fang Dongab,
Xinhua Hec and
Xiaoshuang Laia
aSchool of Water Conservancy and Environment, University of Jinan, Jinan 250022, China. E-mail: hwang_118@163.com; Fax: +86 053182769233; Tel: +86 82767237
bKey Laboratory of Water Resources and Environmental Engineering in Universities of Shandong, Jinan 250022, China
cSchool of Plant Biology, University of Western Australia, Crawley, WA 6009, Australia
First published on 26th June 2018
Identifying the anthropogenic and natural sources of nitrate emissions contributing to surface water continues to be an enormous challenge. It is necessary to control the water quality in the watershed impacted by human disturbance. In this study, water chemical parameters including nitrate (NO3−) concentrations, δ15N–NO3−, δ18O–NO3−, and δ18O–H2O were analyzed to investigate the contamination and sources of NO3− in two watershed rivers (Jinyun, JYN and Jinyang, JYA), Jinan, Shandong, China. Results indicated NO3− concentrations in the JYN were significantly higher than those in the JYA (P < 0.05), probably because of high N input of the extensive farmlands or orchards in the drainage basin. δ15N–NO3− and δ18O–NO3−, associated with Cl−, indicated that nitrate-nitrogen (NO3−–N) was not derived from atmospheric deposition but came principally from manure/sewage and soil organic matter in these two watersheds. The microbial nitrification took place in the nitrate of manure/sewage and soil nitrate. The combination of NO3− concentration and nitrogen and oxygen isotope suggested that NO3− had undergone microbial denitrification after entering the rivers. Furthermore, NO3− concentrations had significant temporal and spatial variation highlighting differential sources and fates. These results expand our understanding of mechanisms driving NO3− retention and transport and provide strategies in managing NO3− contamination in different land use watersheds around the world.
Although the concentration of NO3− and the N-isotopic signature in NO3− have been successfully applied in various case studies of surface and ground waters in widespread watersheds around the world to identify the sources of nitrate-nitrogen (NO3−–N), the wide range and overlapping values for some sources make it difficult to identify the source and transformation of NO3− in surface water and groundwater.12–15 It is promising to employ δ18O–NO3− and δ18O–H2O associated with δ15N–NO3− to differentiate the sources according to the well-established linear model between δ18O–NO3− ranges and microbial nitrification/denitrification.16–18
The rivers flow through different human disturbed watersheds, which could result in the different nitrate level. In this research, the stable isotopes of 15N and 18O in NO3− and δ18O–H2O, in conjunction with land use information and water quality under different land use and anthropogenic activities, were used to characterize the source and transformation of NO3− that delivered to the one important reservoir from two rivers in pairwised watersheds (Jinyun and Jinyang watersheds). The objectives of this research were to determine: (1) if the dissolved NO3− displays significantly seasonal and spatial differences in these two different watersheds; (2) if the water quality and isotopic data could indicate the NO3− sources, i.e., if NO3− originates from fertilizer or manure in the JYN watershed or from organism decomposition or sewage in the JYA watershed; and (3) is there different occurrence of NO3− transformation with the microbial nitrification or denitrification in these two rivers. The possible source of NO3− from fertilizer, manure, septic system, or sewage explanation could be identified due to different land use in these two watersheds. The expected results could provide important base for the risk assessment and management of the nitrate contaminant from the comparable watersheds with different land use practices.
Jinyun river (JYN) and Jinyang river (JYA), locating in southern Jinan city, Shandong, China, are typical watersheds, with a total 55.2 km2 and 181.9 km2 basin areas, respectively. Both rivers together contribute about half of water to the Wohushan reservoir, which supplies the primary drinking water source for 300000 residents in the south central Jinan city and a variety of industrial and agricultural activities of Jinan city (Fig. S1,†).20 The rivers' source originates from the northern slope of Mountain Tai at >1500 m above sea level, and the rivers traverse the southern part of Jinan city before flowing into the Wohushan reservoir (Fig. S1†). Both the JYN and JYA are fed by both precipitation and ground water throughout the year. The input of these two rivers is mainly dominated by surface runoff from local precipitation during the summer rainy season (June to September), whilst, the rivers are sustained by precipitation and seepage of ground water during the remainder of the year. In general, the daily discharge shows a distinct seasonal variation, ranging from 0.67 to 1.26 m3 s−1 in January (winter, lowest) and 4.15 to 7.82 m3 s−1 in August (summer, highest) for both the JYN and JYA (the office of Wohushan reservoir Administration, see website: http://www.whssk.com). The water contribution to the Wohushan reservoir from the JYN watershed is similar to the JYA watershed, whilst their land use and anthropogenic activities are very contrasting. For instance, high N input from chemical fertilizer and manure applications for intensive agricultural activities and orchard plantations are common in the JYN watershed. The NO3− contribution is thus from runoff of precipitation in this watershed. In contrast, more natural tour sites and residential properties are along the JYA watershed. This JYA watershed is thus associated with septic systems and potential point sources of contamination.21
The following equation was used to calculate the δ15N and δ18O values:
δ (‰) = [(Rsample/Rstandard) − 1] × 1000 | (1) |
In order to quantify the measurement, data presentation, calculation and statistical analysis were performed using Microsoft office Excel and SPSS 16.0 (SPSS Inc., USA). The paired t-test and one-way ANOVA were performed at a significant level of P = 0.05.
Seasons | Winter | Spring | Summer | Fall | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Sample sites | Upstream | Middle stream | Downstream | Upstream | Middle stream | Downstream | Upstream | Middle stream | Downstream | Upstream | Middle stream | Downstream | |
a Values reported are means (n = 4) and standard errors in the brackets. The different lowercase letters of a and b in each column of upstream and downstream indicate significant differences between rivers in the same sampling position. | |||||||||||||
T (°C) | JYN | 0.6(0.3)aa | 0.5(0.1)a | 22.5(1.9)a | 22.5(1.2)a | 28.5(2.0)a | 27.2(1.7)a | 16.6(1.5)a | 13.9(2.1)a | ||||
JYA | 0.5(0.1)a | 0.8(0.2) | 0.5(0.1)a | 22.8(0.4)a | 23.6(0.4) | 24.0(0.1)a | 26.5(0.2)a | 26.8(0.3) | 27.0(0.1)a | 13.5(0.1)a | 13.7(0.3) | 13.8(0.2)a | |
IntC | 0.6(0.1)a | 0.5(0.1)a | 23.1(0.3)a | 22.5(0.1)a | 26.8(1.3)a | 27.4(0.1)a | 14.5(0.2)a | 15.2(0.1)a | |||||
pH | JYN | 7.7(0.1)a | 8.1(0.3)a | 8.1(0.1)a | 8.0(0.1)a | 8.0(0.1)a | 7.7(0.2)a | 7.7(0.1)a | 8.1(0.1)a | ||||
JYA | 8.0(0.01)a | 8.1(0.04) | 8.0 (0.02)a | 8.2(0.08)a | 8.0(0.05) | 8.2(0.02)a | 8.0(0.03)a | 7.9(0.02) | 8.0(0.04)a | 7.9(0.03)a | 8.0(0.05) | 8.0(0.02)a | |
IntC | 8.0(0.01)a | 8.0(0.01)a | 8.1(0.03)a | 8.1(0.02)a | 7.9(0.02)a | 8.0(0.01)a | 8.1(0.01)a | 7.9(0.02)a | |||||
DO (mg L−1) | JYN | 14.6(1.5)a | 12.3(1.1)a | 9.7(1.5)a | 8.9(1.2)a | 11.2(1.5)a | 7.0(1.0)a | 10.2(0.9)a | 9.8(1.0)a | ||||
JYA | 12.8(1.2)b | 11.5(1.1) | 15.7(1.4)b | 10.2(1.4)b | 8.8(1.3) | 13.4(1.2)b | 9.4(0.4)b | 8.7(0.8) | 8.2(0.4)a | 9.8(0.3)b | 10.7(1.0) | 10.2(0.2)a | |
IntC | 12.7(1.4)ab | 13.2(1.2)a | 9.6(0.8)a | 8.8(1.1)a | 8.0(1.3)b | 9.2(1.0)a | 9.1(2.2)b | 9.3(1.9)a | |||||
Cl− (mg L−1) | JYN | 27.6(3.2)a | 23.4(2.8)a | 23.9(3.0)a | 24.1(3.4)a | 19.1(1.7)a | 21.0(3.5)a | 19.4(3.2)a | 21.7(2.5)a | ||||
JYA | 25.4(9.2)a | 26.2(0.1) | 27.6(0.03)a | 23.6(0.03)a | 23.0(0.1) | 21.8(0.03)a | 18.1(0.4)a | 16.4(0.3) | 13.6(0.1)a | 20.7(0.1)a | 19.9(0.03) | 20.2(0.5)a | |
IntC | 26.4(5.1)a | 25.8(3.5)a | 23.8(2.8)a | 23.7(4.2)a | 19.2(5.0)a | 18.8(2.7)a | 20.9(3.5)a | 21.2(4.4)a | |||||
NH4+ (mg L−1) | JYN | 0.19(0.02)a | 0.13(0.01)a | 0.14(0.01)a | 0.15(0.03)a | 0.25(0.02)a | 0.65(0.04)a | 0.37(0.02)a | 0.22(0.01)a | ||||
JYA | 0.09(0.01)b | 0.12(0.03) | 0.15(0.01)a | 0.25(0.01)b | 0.12(0.01) | 0.23(0.02)a | 0.13(0.01)b | 0.13 (0.01) | 0.18 (0.01)b | 0.15 (0.01)b | 0.44(0.01) | 0.53(0.03)b | |
IntC | 0.98(0.01)c | 0.12(0.02)a | 0.15(0.09)b | 0.15(0.01)a | 0.37(0.03)a | 0.46(0.03)a | 0.38(0.01)a | 0.39(0.11)a | |||||
NO3− (mg L−1) | JYN | 11.47(0.07)a | 11.00(0.09)a | 6.27(0.05)a | 7.08(0.05)a | 5.56(0.13)a | 4.47(0.15)a | 8.31(0.02)a | 5.76(0.01)a | ||||
JYA | 8.49(0.43)b | 8.92(0.04) | 9.98(0.02)b | 4.73(0.01)b | 3.92(0.01) | 2.48(0.01)b | 6.32(0.16)b | 5.43(0.16) | 5.36(0.09)b | 7.25(0.22)b | 6.05(0.01) | 7.70(0.01)a | |
IntC | 9.87(0.33)b | 10.05(0.29)b | 5.46(0.41)a | 5.21(0.38)b | 5.70(0.22)a | 5.59(0.25)b | 7.21(1.29)b | 7.19(1.03)b | |||||
δ18O–H2O (‰) | JYN | −7.33(1.42)a | −7.92(1.38)a | −9.31(0.38)a | −8.45(0.36)a | −8.34(0.35)a | −7.68(0.33)a | −11.07(2.27)a | −9.22(1.90)a | ||||
JYA | −9.60(0.42)a | −8.15(0.39) | −8.72(0.73)a | −8.73(0.25)a | −9.24(0.43) | −9.08(0.37)a | −9.20(0.23)a | −10.51(0.33) | −8.73(0.51)a | −8.74(0.22)b | −9.45(0.15) | −7.94(0.26)b | |
IntC | −9.20(0.65)a | −7.98(1.14)a | −9.52(0.57)a | −8.19(0.95)a | −8.85(0.48)a | −9.52(0.36)b | −8.76(2.60)b | −9.13(1.58)a | |||||
δ15N–NO3− (‰) | JYN | 6.68(0.09)a | 6.81(0.07)a | 9.39(0.05)a | 9.32(0.04)a | 8.55(0.13)a | 8.73(0.19)a | 7.41(0.01)a | 8.41(0.23) | 4.61(0.02)a | |||
JYA | 8.26(0.29)b | 8.07(0.32) | 8.24(0.27)b | 9.68(0.24)b | 9.35(0.19) | 9.47(0.26)b | 8.25(0.13)b | 8.07(0.17) | 8.15(0.20)b | 8.72(0.22)a | 8.52(0.20)b | ||
IntC | 8.16(0.07)b | 7.86(0.19)a | 9.65(0.08)b | 9.54(0.22)a | 8.24(0.08)b | 8.76(0.17)a | 8.21(0.11)a | 8.35(0.30)b | |||||
δ18O–NO3− (‰) | JYN | 7.31(1.42)a | 7.30(1.40)a | 6.14(0.36)a | 6.65(0.39)a | 8.22(0.33)a | 8.68(0.29)a | 7.43(0.35)a | 5.71(0.28) | 5.11(0.28)a | |||
JYA | 2.89(0.40)b | 3.46(0.42) | 3.25(0.38)b | 6.41(0.54)a | 5.65(0.57) | 6.18(0.52)b | 6.29(0.32)b | 5.84(0.30) | 6.13(0.34)b | 6.13(0.30)b | 6.09(0.31)a | ||
IntC | 5.46(0.52)a | 6.13(0.44)a | 6.52(0.37)a | 7.03(0.55)c | 7.84(0.62)a | 9.21(0.49)b | 6.54(0.35)b | 5.98(0.43)a |
Spatial site | Cl− (mg L−1) | NH4+ (μg L−1) | NO3− (mg L−1) | δ18O–H2O (‰) | δ15N–NO3− (‰) | δ18O–NO3− (‰) |
---|---|---|---|---|---|---|
AVR ± SD | AVR ± SD | AVR ± SD | AVR ± SD | AVR ± SD | AVR ± SD | |
a JYU-U, the upstream Jiyun river; JYU-D, the downstream Jiyun river; JYA-U, the upstream Jiyang river; JYA-M, the middle reach of Jiyang river; JYA-D, the downstream Jiyang river. Values reported are means (n ≥ 12) ± standard errors. The different lowercase letters of a and b in each column indicate significant differences among the sampling positions. | ||||||
JYN-Ua | 22.49 ± 4.08a | 94.84 ± 9.00a | 7.90 ± 2.65a | −9.01 ± 1.59a | 8.01 ± 1.20a | 6.57 ± 1.56a |
JYN-D | 22.58 ± 1.44a | 84.13 ± 9.32b | 7.07 ± 2.82b | −8.32 ± 0.68a | 8.07 ± 1.15a | 6.94 ± 1.48a |
JYA-U | 21.94 ± 3.24a | 85.84 ± 5.33a | 6.70 ± 1.58b | −9.07 ± 0.42a | 8.73 ± 0.67a | 5.43 ± 1.70a |
JYA-M | 21.38 ± 4.21a | 88.08 ± 11.56b | 6.08 ± 2.09b | −9.34 ± 0.97a | 8.46 ± 0.61a | 5.17 ± 1.14b |
JYA-D | 20.78 ± 5.75a | 84.41 ± 16.50b | 6.38 ± 3.21a | −8.62 ± 0.48a | 8.60 ± 0.60a | 5.41 ± 1.44a |
Integrated channel | 22.46 ± 2.90a | 90.36 ± 9.31b | 7.24 ± 1.96c | −8.89 ± 0.57a | 8.60 ± 0.67 ab | 6.84 ± 1.20a |
Fig. 1 Plots of NO3− and Cl− in the Jinyun river and Jinyang river and integrated channel of Jinan, China. |
The nitrate concentration in JYA is lower than JYN during winter, spring and fall, but higher than JYN during summer. This nitrate seasonal variation corresponds to the seasonal variation of nitrogen isotope and oxygen isotope, which displayed high nitrate concentration with high nitrogen isotopes and low oxygen isotope. The results showed that the possible nitrate sources is from manure or sewage waste. The possible reasons are that there are more agricultural lands distributed in the subwatershed of JYN. The application of manures and runoff in the summer may result in the drastic disturbance.
The Cl− concentrations in JYN and JYA were distinctly higher than in the precipitation (Fig. 1). It was primarily concluded that NO3− were not only from precipitation. δ15N–NO3− values varied between +4.61 and +9.39‰ (averaged 8.54 ± 0.92‰, n = 56, Tables 1 and 2) and were lower in the upstream (JYN-U, 8.01 ± 1.20‰) than in the downstream (JYN-D, 8.07 ± 1.15‰) of the Jinyun river (Fig. 2A). δ15N–NO3− values were not significantly different among the upstream of the Jinyang river (JYA-U, averaged 7.33‰), the middle reach of the Jinyang river (JYA-M, averaged 7.08‰), and the downstream of the Jinyang river (JYA-D, averaged 8.02‰); they varied between +8.07–9.68‰ (Fig. 2A). Across these spatial river sites, δ15N–NO3− values were significantly higher in spring than other seasons (Fig. 2B). The addition of NO3− from manure or sewage might produce elevations of both the NO3− concentration and the δ15N–NO3− signature.7 In this study, although the runoff of precipitation is more drastic in summer than other season, δ15N–NO3− was not higher in the summer. This indicated that NO3− from discharged sewage may be the main sources.
Fig. 2 NO3− versus δ15N–NO3− in spatial sites of these two watershed rivers (A) and in different seasons across the watersheds (B). The ranges in A are from Isotope Hydrology (Joel R Gat, 2010). |
The combination of analyzing the concentration and the isotopic composition of NO3− is a useful tool to identify the NO3− source and the denitrification process in a watershed.17,18,25 Values of NO3− and δ15N–NO3− were widely scattered in both the JYN and JYA (Fig. 2A). Values of δ15N–NO3− for these two rivers were not significantly different by paired t-test (P = 0.22). The integrated channel showed similar patterns and the values were between the JYN and JYA rivers, reflecting the mixing of these two rivers (Table 1).
The ranges of δ15N–NO3− indicated the NO3− originated primarily from the manure or sewage, with only a little from NO3− fertilizer in the JYN. However, the NO3− concentrations did not increase with δ15N–NO3− (Fig. 2A and B). Therefore, it was likely that the state of NO3− from manure or sewage changed with nitrification and denitrification controlled by microbes.
Fig. 3 Patterns of δ18O–H2O and δ18O–NO3− for the Jinyun river and Jinyang river in different seasons. |
Although all δ18O–NO3− values fell in the range typically cited as representing ammonium fertilizer sources (−8‰ < δ18O–NO3− < +14‰), whilst, δ15N–NO3− values were out of the range for ammonium fertilizer sources (−7‰ < δ15N–NO3− < +5‰).26,27 The δ18O–NO3− values produced by microbial nitrification in watersheds range from −10 to +10‰ (Kendall et al., 2007).16 All of these sample values had some overlap range of typical soil nitrate (+3‰ < δ15N–NO3− < +8‰, −8‰ < δ18O–NO3−< +14‰). Soil NO3− is a product of bacterial decomposition of organic N that results from the decomposition of plants and animals and their products (i.e. organic waste). Inorganic or organic N based fertilizers are a primary source of nitrate in agricultural areas, while septic waste plays a significant role in residential areas.18,28 The results indicated that the NO3− for these two rivers could be derived from the nitrification of manure/sewage other than ammonium fertilizers.26–28 Furthermore, it did support our hypothesis that different land uses could result in different NO3− sources in these two rivers. However, there was no information available on the rates of various fractionation processes, the usage of manure in these two watersheds, or the amount of sewage discharging to the JYN and JYA, and therefore soil NO3− could not be separated from other NO3− sources derived from based on δ15N–NO3− values alone.
δ18O–NO3− values in these two rivers were within −10 to +10‰ (Fig. 2B), possibly suggesting that most of NO3− contributed by soil nitrate could be from microbial nitrification before flowing into the JYN and JYA. Nitrogen-fixing bacteria account for two-thirds of the oxygen atoms in NO3− from soil water and one-third from atmospheric oxygen.29,30 As shown in Fig. 4, the δ18O–NO3− and δ18O–H2O values in these two rivers were highly and positively correlated (r2 = 0.393, P = 0.04), further suggesting that the δ18O–NO3− values were largely controlled by the δ18O–H2O in the river during the microbial nitrification. However, there was no regular seasonal distribution of δ18O–H2O in these two rivers compared with the oxygen isotopic composition of dissolved NO3−, indicating that the nitrification capacity from microbial activities might not be always consistent with the seasons change (Fig. 4). The correlations between the δ18O–NO3− and δ18O–H2O in the spring and autumn are better than the summer and winter. The possible reasons are the temperatures and water quantities in these two seasons are apt to the microbial nitrification in the river.
Fig. 4 Patterns of δ18O–H2O and δ18O–NO3− for the Jinyun river and Jinyang river in different seasons. |
Denitrification can occur in anaerobic pockets within a water body and can cause a characteristic increase of both the δ15N–NO3− and δ18O–NO3− values in the remaining NO3−.16,31 The process of ammonia evaporation causes an enrichment of heavier N isotope and hence increases the δ15N values.7,16 Indeed, these changes of isotopic compositions would correlate with decreasing NO3− concentrations as nitrate is being transformed to nitrogen gas and then out of the system. It is important to validate whether the observed changes in the isotopic composition of the remaining NO3− correspond to a decrease of the total dissolved NO3− in the water body. This can be done by plotting δ15N against a concentration scale.32 Although the ratio of changes in δ15N–NO3− and δ18O–NO3− is not typically close to 1:2, the δ15N–NO3− values across these two river water negatively correlated with NO3− in the winter in this study (Fig. 2B). The variation in the negative correlation between δ15N–NO3− and NO3− concentrations showed that the denitrification had happened although the dissolved oxygen is higher in the winter river (Kendall, 1998).26
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c8ra04364g |
This journal is © The Royal Society of Chemistry 2018 |